·Vector Optimization: new concepts of e-efficiency and level sets of abstract optimization problems, which are applied to obtain various versions of variational principles, and to establish well-posedness of vector optimization problems.

·Parametric Optimization: optimization problems whose data are smooth functions of a parameter; singularity theory of the stationary solutions to the parametric problems; regularity as a generic property; path-following methods

·Statistical Analysis: delta theorems of first and higher order for random sets in infinite dimensional spaces and their selections; statistical tests for stochastic dominance; estimation of measures of risk and Lorenz functions.